Senior Data Scientist, Biologics Discovery – AI-Driven

Johnson Johnson; United States; On-site; USD 109,000 - 175,000; Full time

Benefits offered by this job

Medical benefits

Dental & Vision

Life insurance

Retirement plan

Job summary

Johnson & Johnson Innovative Medicine seeks a Senior Data Scientist dedicated to Biologics Discovery. This role sits with the Data Science team and partners closely with In Silico Discovery to build molecular design and property-prediction models and data-facing ML capabilities.

You will design robust featurization, curate model-ready datasets, and collaborate with Discovery scientists to prioritize molecules, flag risks, and generate hypotheses for faster, more reliable AI-driven biology.

Qualifications

• Master’s or Ph.D. in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Statistics, or related field.
• At least 2 years of applied ML experience with model development and dataset curation on complex scientific data.
• Strong proficiency with Python and the modern ML stack (PyTorch, scikit-learn) and SQL.
• Experience turning heterogeneous experimental data into robust features with cloud training exposure.
• Knowledge of evaluation, validation, and leakage risks; ability to collaborate in a matrixed R&D environment.

Responsibilities

• Design featurization and curate model-ready datasets from biologics data.
• Collaborate with Discovery scientists to frame ML problems around DMTL cycles.
• Work with data engineers to specify features, labels, and aggregation levels for models.
• Champion reproducibility, documentation, and responsible AI.

Skills

Python

PyTorch

Scikit-learn

SQL

ML Pipelines

Education

Master’s or Ph.D. in CS/ML/Computational Biology

Tools

MLOps

Job description

Johnson & Johnson Innovative Medicine seeks a Senior Data Scientist dedicated to Biologics Discovery. This role sits with the Data Science team and partners closely with In Silico Discovery to build molecular design and property-prediction models and data-facing ML capabilities.

You will design robust featurization, curate model-ready datasets, and collaborate with Discovery scientists to prioritize molecules, flag risks, and generate hypotheses for faster, more reliable AI-driven biology.